pacman::p_load(sf, sfdep, tmap, tidyverse, spNetwork, spacetime, spatstat, ggplot2)Take-home Exercise 1
Setting the Scene
As urbanization increases globally, cities are becoming more congested with vehicles, leading to a higher incidence of traffic accidents. Effective urban planning and road safety interventions rely on a deep understanding of where and when accidents are most likely to occur. The ability to identify traffic hotspots and patterns over time is critical for city authorities and policymakers to develop more targeted safety measures.
In this study, we examine the traffic accident data for the Bangkok Metropolitan Region (BMR), one of Southeast Asia’s largest urban conglomerations. The analysis focuses on spatial and temporal dimensions to identify accident hotspots across different road networks. Using Kernel Density Estimation (KDE) and Network Constrained K-function analysis, we aim to detect areas of high risk and analyze how accident patterns vary across time periods (e.g., day vs. night, weekdays vs. weekends).
This project builds on advanced geospatial analysis techniques and is designed to provide critical insights into the spatial concentration of traffic accidents. The results will help decision-makers identify the most accident-prone areas and develop interventions to reduce the risk of accidents in these hotspots.
Objectives
The main objective of this take-home exercise is to explore spatio-temporal dynamics and identify traffic accident hotspots in the Bangkok Metropolitan Region (BMR). The specific goals are:
Accident Hotspot Detection: Use Kernel Density Estimation (KDE) to visualize and detect areas of high accident density across the BMR road network. This will be done both at a regional level and for selected high-risk provinces (e.g., Bangkok and Samut Prakan).
Spatio-Temporal Analysis: Perform temporal analysis by splitting the data into different time periods (e.g., day vs. night, weekdays vs. weekends) to understand how accident patterns evolve over time.
Network Constrained Analysis: Apply Network Constrained Kernel Density Estimation (NKDE) and K-function analysis to detect clustering patterns of accidents on road networks. This analysis will help understand how accidents are distributed along specific road networks and identify clusters of incidents.
Visualization and Reporting: Use geospatial visualization tools to effectively communicate findings. This includes generating interactive heatmaps and visual comparisons of accident density for different time periods and road networks.
The Data
Road Accident Data (2019-2022): This dataset includes information on over 12,986 road accidents that occurred in the BMR region. Each entry contains detailed information such as the time and location of the incident, the type of road, and other contextual factors. The key attributes in this dataset include:
incident_datetime: The date and time when the accident occurred. province: The province where the accident took place. road_type: Information about the road category where the accident occurred (e.g., highways, secondary roads). Bangkok Metropolitan Region Roads (from OpenStreetMap): The road network data includes detailed geographical information on the roads in the BMR. The dataset provides the structure of roads as LINESTRING geometries and includes information on road types, length, and geometry details.
Thailand Subnational Administrative Boundaries: This dataset includes the administrative boundaries of the provinces in the BMR. It allows for an understanding of accident distributions across different administrative regions (e.g., Bangkok, Samut Prakan, Pathum Thani, etc.).
The combination of these datasets enables us to perform detailed geospatial analysis, including network-based density estimations and spatial clustering detection. The accident data is pre-processed to clean any inconsistencies and transformed to appropriate coordinate reference systems (CRS) to align with road network data.
Getting Started
To begin, several R packages are loaded for different purposes such as spatial data processing, network analysis, and visualization:
sf (Simple Features): Provides tools for manipulating and analyzing spatial data, specifically through sf objects which store geometries like points, lines, and polygons.
sfdep: Used for spatial dependence analysis, including functions for working with neighbors and performing spatial lag models. tmap: A package designed for creating both static and interactive maps. It offers tools for geospatial data visualization, which is critical for this analysis to present accident hotspots and spatial patterns effectively. tidyverse: A collection of R packages that simplifies data manipulation, visualization, and exploration through functions like dplyr, ggplot2, and tibble.
spNetwork: A specialized package for network-based spatial analysis. It supports functions like network-constrained Kernel Density Estimation (NKDE) and network-constrained K-function analysis.
spacetime: Provides classes and methods for spatio-temporal data, allowing analysis over both space and time. stpp: Designed for space-time point process modeling and simulation. Useful for detecting spatio-temporal clusters and patterns in the accident data.
spatstat: A package for spatial point pattern analysis, providing tools for calculating K-functions and conducting spatial statistics over road networks.
##Importing Data ### 1. Load and Clean Accident Data
car_acc <- read_csv("data/rawdata/thai_road_accident_2019_2022.csv") %>%
# Remove rows with missing longitude or latitude
filter(!is.na(longitude) & !is.na(latitude)) %>%
# Create new columns for month and day of the week
mutate(Month_num= month(incident_datetime)) %>%
mutate(Month_fac= month(incident_datetime,label=TRUE,abbr=TRUE))%>%
mutate(dayofweek=day(incident_datetime))%>%
# Convert the data frame to a spatial sf object
st_as_sf(coords = c("longitude", "latitude"), crs = 4326) %>%
# Transform to a different CRS (Coordinate Reference System)
st_transform(crs = 32647)read_csv(): Reads the CSV file containing the road accident data. filter(!is.na(longitude) & !is.na(latitude)): Removes any rows where either longitude or latitude is missing, ensuring valid spatial data. mutate(Month_num = month(incident_datetime)): Creates a new column Month_num that extracts the month from the incident_datetime column. mutate(Month_fac = month(incident_datetime, label = TRUE, abbr = TRUE)): Creates a new column Month_fac that formats the month as a labeled and abbreviated factor. mutate(dayofweek = day(incident_datetime)): Creates a new column dayofweek that extracts the day of the month from incident_datetime. st_as_sf(coords = c(“longitude”, “latitude”), crs = 4326): Converts the data into a spatial object with coordinates based on longitude and latitude. CRS 4326 is the WGS84 geographic coordinate system. st_transform(crs = 32647): Transforms the spatial object to UTM zone 47N (EPSG: 32647), which is often used for geographic data in Thailand.
2. Filter Accident Data for BMR (Bangkok Metropolitan Region)
bmr_acc <- car_acc %>%
filter(province_en %in% c("Bangkok", "Nonthaburi", "Nakhon Pathom", "Pathum Thani", "Samut Prakan", "Samut Sakhon"))filter(province_en %in% c(…)): Filters the accident data to include only accidents occurring in the Bangkok Metropolitan Region, i.e., the six listed provinces.
3. Save the Filtered Data for BMR
##| eval: false
write_rds(bmr_acc,"data/rds/bmr_acc.rds")4. Load Administrative Boundaries
##| eval: false
boundaries <- st_read(dsn = "data/rawdata",
layer = "tha_admbnda_adm1_rtsd_20220121")Reading layer `tha_admbnda_adm1_rtsd_20220121' from data source
`/Users/lucasluo/Desktop/SMU/Courses/Term3 Aug-Dec/ISSS626-Geospatial Analytics and Applications/lucasluo6/ISSS626/Take-home_Ex/Take-home_Ex01/data/rawdata'
using driver `ESRI Shapefile'
Simple feature collection with 77 features and 16 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 97.34336 ymin: 5.613038 xmax: 105.637 ymax: 20.46507
Geodetic CRS: WGS 845. Filter Boundaries for BMR
bmr_boundary <- boundaries %>%
filter(ADM1_EN %in% c("Bangkok", "Nonthaburi", "Nakhon Pathom", "Pathum Thani", "Samut Prakan", "Samut Sakhon"))6. Save Filtered BMR Boundaries
write_rds(bmr_boundary, "data/rds/bmr.rds")7. Load Road Network Data
roads <- st_read(dsn = "data/rawdata",
layer = "hotosm_tha_roads_lines_shp")Reading layer `hotosm_tha_roads_lines_shp' from data source
`/Users/lucasluo/Desktop/SMU/Courses/Term3 Aug-Dec/ISSS626-Geospatial Analytics and Applications/lucasluo6/ISSS626/Take-home_Ex/Take-home_Ex01/data/rawdata'
using driver `ESRI Shapefile'
Simple feature collection with 2792590 features and 14 fields
Geometry type: MULTILINESTRING
Dimension: XY
Bounding box: xmin: 97.34457 ymin: 5.643645 xmax: 105.6528 ymax: 20.47168
CRS: NA8. Assign CRS to Road Network
##| eval: false
st_crs(roads) <- 43269. Clip Roads to BMR Boundaries
##| eval: false
bmr_roads <- st_intersection(roads, bmr_boundary)10. Save the Filtered BMR Roads Data
##| eval: false
saveRDS(bmr_roads,"data/rds/bmr_roads.rds")11. Load the Date from RDS
bmr <- read_rds("data/rds/bmr.rds")
bmrSimple feature collection with 6 features and 16 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 99.8141 ymin: 13.4252 xmax: 100.9639 ymax: 14.27595
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF
1 2.417227 0.13133873 Bangkok กรุงเทพมหานคร TH10 <NA>
2 1.695100 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA>
3 1.251111 0.05323766 Nonthaburi นนทบุรี TH12 <NA>
4 1.884945 0.12698345 Pathum Thani ปทุมธานี TH13 <NA>
5 2.463030 0.17891420 Nakhon Pathom นครปฐม TH73 <NA>
6 1.566369 0.07155983 Samut Sakhon สมุทรสาคร TH74 <NA>
ADM1ALT1EN ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE
1 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
2 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
3 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
4 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
5 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
6 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
date validOn validTo geometry
1 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.6139 13...
2 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.7306 13...
3 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.3415 14...
4 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.8916 14...
5 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.2231 14...
6 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.3091 13...bmr_roads <- read_rds("data/rds/bmr_roads.rds")
bmr_roadsSimple feature collection with 585597 features and 30 fields
Geometry type: GEOMETRY
Dimension: XY
Bounding box: xmin: 99.81436 ymin: 13.42543 xmax: 100.9637 ymax: 14.27563
Geodetic CRS: WGS 84
First 10 features:
name name_en highway surface smoothness
1 ถนนฉลองกรุง Chalong Krung Road secondary paved <NA>
2 ซอยฉลองกรุง 1/1 Soi Chalong Krung 1/1 residential <NA> <NA>
3 <NA> <NA> secondary_link <NA> <NA>
4 <NA> <NA> service <NA> <NA>
5 ถนนฉลองกรุง Chalong Krung Road secondary concrete <NA>
6 <NA> <NA> service <NA> <NA>
26 <NA> <NA> footway <NA> <NA>
27 <NA> <NA> service <NA> <NA>
49 <NA> <NA> service concrete excellent
50 <NA> <NA> service <NA> <NA>
width lanes oneway bridge layer source name_th osm_id osm_type
1 <NA> <NA> yes <NA> <NA> <NA> ถนนฉลองกรุง 1125681229 ways_line
2 <NA> <NA> <NA> <NA> <NA> <NA> ซอยฉลองกรุง 1/1 594401607 ways_line
3 <NA> <NA> yes <NA> <NA> <NA> <NA> 472283206 ways_line
4 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 594401608 ways_line
5 <NA> 2 yes yes 1 Bing ถนนฉลองกรุง 116847248 ways_line
6 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 317485095 ways_line
26 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 879520330 ways_line
27 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 879520327 ways_line
49 <NA> <NA> yes <NA> <NA> <NA> <NA> 453683945 ways_line
50 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 630845598 ways_line
Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN
1 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
2 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
3 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
4 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
5 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
6 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
26 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
27 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
49 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
50 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE date
1 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
2 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
3 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
4 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
5 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
6 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
26 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
27 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
49 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
50 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
validOn validTo geometry
1 2022-01-22 <NA> LINESTRING (100.7913 13.740...
2 2022-01-22 <NA> LINESTRING (100.7882 13.736...
3 2022-01-22 <NA> LINESTRING (100.7844 13.732...
4 2022-01-22 <NA> LINESTRING (100.7873 13.735...
5 2022-01-22 <NA> LINESTRING (100.7831 13.730...
6 2022-01-22 <NA> LINESTRING (100.7931 13.746...
26 2022-01-22 <NA> LINESTRING (100.7716 13.741...
27 2022-01-22 <NA> LINESTRING (100.7737 13.744...
49 2022-01-22 <NA> LINESTRING (100.5607 13.749...
50 2022-01-22 <NA> LINESTRING (100.5261 13.721...bmr_acc <- read_rds("data/rds/bmr_acc.rds")
bmr_accSimple feature collection with 12986 features and 19 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 591277.5 ymin: 1486846 xmax: 710166.1 ymax: 1576520
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 12,986 × 20
acc_code incident_datetime report_datetime province_th province_en
* <dbl> <dttm> <dttm> <chr> <chr>
1 571882 2019-01-01 02:25:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
2 600001 2019-01-01 03:00:00 2019-01-05 10:33:00 นนทบุรี Nonthaburi
3 605043 2019-01-01 03:00:00 2019-03-29 08:22:00 สมุทรปราการ Samut Prakan
4 629691 2019-01-01 03:05:00 2019-01-01 03:05:00 กรุงเทพมหานคร Bangkok
5 571887 2019-01-01 04:30:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
6 599234 2019-01-01 04:45:00 2019-01-02 08:28:00 สมุทรปราการ Samut Prakan
7 599990 2019-01-01 05:30:00 2019-01-05 10:35:00 สมุทรสาคร Samut Sakhon
8 612045 2019-01-01 05:30:00 2019-10-09 13:50:00 นนทบุรี Nonthaburi
9 629689 2019-01-01 05:42:00 2019-01-01 05:42:00 กรุงเทพมหานคร Bangkok
10 607046 2019-01-01 06:30:00 2019-05-15 13:24:00 ปทุมธานี Pathum Thani
# ℹ 12,976 more rows
# ℹ 15 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <int>,
# geometry <POINT [m]>EDA (Exploratory Data Analysis)
The EDA focuses on visualizing the basic geographic features and accident points within the Bangkok Metropolitan Region (BMR). Here’s a breakdown of each component of the code and the result:
EDA 1: Visualization of Traffic Accidents in the BMR
tm_shape(bmr) +
tm_polygons() + # 绘制BMR的区域边界
tm_shape(bmr_roads) +
tm_lines() + # 绘制BMR区域内的道路
tm_shape(bmr_acc) +
tm_dots(col = "red", size = 0.1) + # 绘制BMR区域内的交通事故点
tm_layout(title = "Road Traffic Accidents in BMR")
# 切换到交互模式
tmap_mode("plot")Explanation of the Code: tm_shape(bmr) + tm_polygons():
This part of the code visualizes the boundary of the BMR region by using the polygon data from bmr. The boundary defines the geographic limits of the region under analysis. tm_shape(bmr_roads) + tm_lines():
This adds the road network to the visualization. The roads are crucial for understanding the spatial relationship between the accident locations and the infrastructure in the region. tm_shape(bmr_acc) + tm_dots(col = “red”, size = 0.1):
This plots the accident locations on the map as red dots. The small dot size ensures that even when multiple accidents occur close to each other, the map remains readable. tm_layout(title = “Road Traffic Accidents in BMR”):
This switches the map into interactive mode, allowing users to zoom, pan, and explore the geographic data more dynamically. Result Analysis: Accident Distribution: The red dots represent individual traffic accidents in the BMR. The visualization clearly shows that the accidents are concentrated along the major roads and highways, suggesting that higher traffic volumes and more complex intersections may be contributing to the occurrence of accidents. High-risk Areas: Some road segments appear to have a dense cluster of accidents, which could indicate accident-prone areas. These could be major intersections, busy highways, or areas with challenging road conditions.
EDA 2: Monthly Distribution of Traffic Accidents in BMR
# 按月分组，计算每个月的事故数量
monthly_accidents <- bmr_acc %>%
group_by(Month_fac) %>%
summarise(count = n())
# 使用 tmap 显示按月的事故分布 (静态模式)
tmap_mode("plot") # 切换到静态模式
# 绘制按月的事故分布
tm_shape(bmr) +
tm_borders() + # 显示 BMR 边界
tm_shape(bmr_acc) +
tm_dots(col = "Month_fac", palette = "Reds", size = 0.05) + # 显示事故点，按月分类
tm_facets(by = "Month_fac", free.coords = FALSE) + # 每个月显示一张静态地图
tm_layout(title = "Accidents by Month in BMR")
This visualization illustrates the monthly distribution of traffic accidents in the Bangkok Metropolitan Region (BMR). Accidents are grouped and color-coded by month, showing how accident occurrences vary across the calendar year. This helps in identifying temporal patterns and trends related to seasonal factors, road usage, or external influences (e.g., weather, holidays) that may contribute to the increase or decrease in accidents during specific months. The map uses a facet approach, allowing for a detailed month-by-month comparison, making it easier to visually assess changes in accident distribution across different time periods.
EDA 3: Heatmap of Traffic Accident Density in BMR Provinces
# 1. 处理省份名称的不一致问题，确保 bmr 和 bmr_acc 的省份名称一致
bmr$ADM1_EN <- trimws(tolower(bmr$ADM1_EN))
bmr_acc$province_en <- trimws(tolower(bmr_acc$province_en))
# 2. 检查省份名称的差异，手动修正任何差异
setdiff(bmr$ADM1_EN, bmr_acc$province_en)character(0)setdiff(bmr_acc$province_en, bmr$ADM1_EN)character(0)# 如果发现不匹配的省份名称，手动修正，例如：
# bmr_acc <- bmr_acc %>%
# mutate(province_en = ifelse(province_en == "some_mismatch", "correct_name", province_en))
# 3. 计算每个省份的事故数量
accidents_by_province <- bmr_acc %>%
group_by(province_en) %>%
summarise(accident_count = n())
# 4. 将数据合并到BMR区域的几何数据
bmr_df <- st_drop_geometry(bmr)
# 确保省份名称格式一致
accidents_by_province <- accidents_by_province %>%
mutate(province_en = tolower(province_en))
bmr_df <- bmr_df %>%
mutate(ADM1_EN = tolower(ADM1_EN))
# 使用 left_join() 进行合并
bmr_with_accidents <- left_join(bmr_df, accidents_by_province, by = c("ADM1_EN" = "province_en"))
# Reorder columns to ensure ADM1_EN is the first
bmr_with_accidents <- bmr_with_accidents %>%
select(ADM1_EN, everything())
# 创建热力图，刻度均匀分布，鼠标悬停时显示事故数量
# 4. 合并数据时确保省份名称字段正确
bmr_with_accidents_sf <- st_as_sf(bmr_with_accidents, geometry = bmr$geometry)
# 创建交互式热力图，设置 popup.vars
tm_shape(bmr_with_accidents_sf) +
tm_polygons("accident_count",
style = "pretty",
palette = "Reds",
title = "Accidents per Province",
popup.vars = c("Province" = "ADM1_EN", "Accidents" = "accident_count"),
popup.format = list(digits = 0)) +
tm_layout(title = "Accident Count Heatmap in BMR", legend.format = list(text.separator = "-"))
tmap_mode("view")Explanation: Data Preparation:
Accident Data Processing: We started by reading in the accident dataset and filtering out rows where the coordinates (latitude, longitude) were missing. We then extracted the relevant date components (month and day of the week) from the accident timestamps for future analysis. The dataset was then converted into a spatial object using the appropriate geographic coordinate system (CRS 4326). Boundary and Road Data: Similarly, we read in the boundary and road data for the entire country of Thailand. We filtered out only the relevant provinces that belong to the Bangkok Metropolitan Region (BMR), which includes Bangkok, Nonthaburi, Nakhon Pathom, Pathum Thani, Samut Prakan, and Samut Sakhon. The roads were intersected with the BMR boundary to limit them to the region we are interested in. Province-Level Accident Count:
Standardization of Names: Before merging the datasets, we ensured consistency in the naming of provinces across the two datasets (bmr and bmr_acc). We converted all province names to lowercase and removed any extra spaces. Accident Count: We then grouped the accident data by province and counted the total number of accidents for each province. Merging Data:
We merged the accident counts with the BMR boundary data to assign the accident data to the spatial geometry of each province. This allows us to visually analyze accident density within each province. Visualization:
We used the tmap library to create an interactive heatmap. The accident density for each province is color-coded in shades of red, where darker shades indicate higher accident counts. Hovering over a province will display the exact count of accidents for that region. Result Analysis: The heatmap generated from the data analysis allows us to visually assess which provinces in the BMR have higher accident densities. The interactive aspect lets users hover over each province to see the accident count, making it easy to compare different regions. Key observations from this visualization could include:
Bangkok likely has the highest density of accidents due to its high population density and traffic volume. Samut Prakan and Nonthaburi may also show significant accident counts due to their proximity to Bangkok and the presence of major highways. Further analysis can be done by looking into different time periods (day vs. night, weekdays vs. weekends) or by exploring specific road networks using KDE methods to identify high-risk areas. The insights gained from this analysis can help in urban planning, improving road safety measures, and optimizing traffic management to reduce accidents in high-density areas.
##Network KDE (NKDE) Analysis
1.data ：
# 假设 bmr_roads 和 bmr 已经被读取并转换为 sf 对象
bmr_roads <- bmr_roads %>%
filter(highway %in% c("motorway", "trunk", "primary", "secondary"))
# 假设 adm_data 是包含 Samut Prakan 和 Bangkok 的边界数据
bmr_city <- st_read(dsn = "data/rawdata",
layer = "tha_admbnda_adm2_rtsd_20220121")Reading layer `tha_admbnda_adm2_rtsd_20220121' from data source
`/Users/lucasluo/Desktop/SMU/Courses/Term3 Aug-Dec/ISSS626-Geospatial Analytics and Applications/lucasluo6/ISSS626/Take-home_Ex/Take-home_Ex01/data/rawdata'
using driver `ESRI Shapefile'
Simple feature collection with 928 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 97.34336 ymin: 5.613038 xmax: 105.637 ymax: 20.46507
Geodetic CRS: WGS 84# Step 1: 筛选出 ADM1_EN 为 Samut Prakan 和 Bangkok 的道路数据
SamutPrakan_roads <- bmr_roads %>%
filter(ADM1_EN == "Samut Prakan")
bangkok_roads <- bmr_roads %>%
filter(ADM1_EN == "Bangkok")
# Step 2: 使用 st_intersection 进行空间相交
# 确保 Samut Prakan 和 Bangkok 的边界数据存在于 bmr 中，且为 sf 对象
SamutPrakan_boundary <-bmr_city %>%
filter(ADM1_EN == "Samut Prakan")
bangkok_boundary <- bmr_city %>%
filter(ADM1_EN == "Bangkok")
# 对 Pathum Thani 进行空间相交
SamutPrakan_roads_intersection <- st_intersection(SamutPrakan_roads,SamutPrakan_boundary)
# 对 Bangkok 进行空间相交
bangkok_roads_intersection <- st_intersection(bangkok_roads, bangkok_boundary)
# 查看结果
print(SamutPrakan_roads_intersection)Simple feature collection with 1612 features and 49 fields
Geometry type: GEOMETRY
Dimension: XY
Bounding box: xmin: 100.4465 ymin: 13.4883 xmax: 100.9543 ymax: 13.71692
Geodetic CRS: WGS 84
First 10 features:
name name_en highway surface smoothness width lanes
90392 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> <NA>
90393 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> <NA>
90394 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> <NA>
90863 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> 3
90864 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> 5
90865 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> <NA>
90945 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> 5
130350 ถนนเทพารักษ์ Thepharak Road secondary <NA> <NA> <NA> 3
130386 ถนนแพรกษา Phraek Sa Road secondary concrete <NA> <NA> 3
131577 ถนนศรีนครินทร์ Srinagarindra Road primary <NA> <NA> <NA> 5
oneway bridge layer source name_th osm_id osm_type Shape_Leng
90392 yes yes 1 <NA> ถนนเทพารักษ์ 746408862 ways_line 1.6951
90393 yes yes 1 <NA> ถนนเทพารักษ์ 746408863 ways_line 1.6951
90394 yes yes 1 <NA> ถนนเทพารักษ์ 746408890 ways_line 1.6951
90863 yes <NA> <NA> <NA> ถนนเทพารักษ์ 1041621544 ways_line 1.6951
90864 yes <NA> <NA> <NA> ถนนเทพารักษ์ 1041623692 ways_line 1.6951
90865 yes <NA> <NA> <NA> ถนนเทพารักษ์ 1041623693 ways_line 1.6951
90945 yes <NA> <NA> <NA> ถนนเทพารักษ์ 1041623694 ways_line 1.6951
130350 yes <NA> <NA> <NA> ถนนเทพารักษ์ 1041621536 ways_line 1.6951
130386 yes <NA> <NA> <NA> ถนนแพรกษา 950318416 ways_line 1.6951
131577 yes <NA> <NA> <NA> ถนนศรีนครินทร์ 1041607912 ways_line 1.6951
Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN
90392 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
90393 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
90394 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
90863 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
90864 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
90865 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
90945 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
130350 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
130386 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
131577 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE
90392 <NA> <NA> <NA> Thailand ประเทศไทย TH
90393 <NA> <NA> <NA> Thailand ประเทศไทย TH
90394 <NA> <NA> <NA> Thailand ประเทศไทย TH
90863 <NA> <NA> <NA> Thailand ประเทศไทย TH
90864 <NA> <NA> <NA> Thailand ประเทศไทย TH
90865 <NA> <NA> <NA> Thailand ประเทศไทย TH
90945 <NA> <NA> <NA> Thailand ประเทศไทย TH
130350 <NA> <NA> <NA> Thailand ประเทศไทย TH
130386 <NA> <NA> <NA> Thailand ประเทศไทย TH
131577 <NA> <NA> <NA> Thailand ประเทศไทย TH
date validOn validTo Shape_Leng.1 Shape_Area.1
90392 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
90393 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
90394 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
90863 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
90864 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
90865 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
90945 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
130350 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
130386 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
131577 2019-02-18 2022-01-22 <NA> 0.822417 0.01436481
ADM2_EN ADM2_TH ADM2_PCODE ADM2_REF ADM2ALT1EN
90392 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
90393 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
90394 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
90863 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
90864 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
90865 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
90945 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
130350 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
130386 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
131577 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA> <NA>
ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH ADM1_EN.1 ADM1_TH.1 ADM1_PCODE.1
90392 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
90393 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
90394 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
90863 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
90864 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
90865 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
90945 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
130350 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
130386 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
131577 <NA> <NA> <NA> Samut Prakan สมุทรปราการ TH11
ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1 date.1 validOn.1 validTo.1
90392 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
90393 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
90394 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
90863 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
90864 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
90865 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
90945 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
130350 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
130386 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
131577 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
90392 LINESTRING (100.6518 13.617...
90393 LINESTRING (100.6517 13.617...
90394 LINESTRING (100.6695 13.611...
90863 LINESTRING (100.6269 13.627...
90864 LINESTRING (100.6273 13.627...
90865 LINESTRING (100.6275 13.627...
90945 LINESTRING (100.6287 13.626...
130350 LINESTRING (100.627 13.6275...
130386 LINESTRING (100.6315 13.575...
131577 LINESTRING (100.6206 13.614...print(bangkok_roads_intersection)Simple feature collection with 8624 features and 49 fields
Geometry type: GEOMETRY
Dimension: XY
Bounding box: xmin: 100.3309 ymin: 13.51917 xmax: 100.9345 ymax: 13.95438
Geodetic CRS: WGS 84
First 10 features:
name name_en highway surface smoothness
10909 ถนนจักรเพชร Chakkraphet Road secondary <NA> <NA>
62066 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road primary asphalt <NA>
62124 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road primary <NA> <NA>
62126 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road primary asphalt <NA>
62133 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road primary asphalt <NA>
62134 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road secondary asphalt <NA>
62142 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road primary asphalt <NA>
62143 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road primary asphalt <NA>
62149 ถนนราชดำเนินกลาง Ratchadamnoen Klang Road secondary asphalt <NA>
62150 ถนนราชดำเนินนอก Ratchadamnoen Nok Road secondary asphalt <NA>
width lanes oneway bridge layer source name_th osm_id
10909 <NA> <NA> yes <NA> <NA> <NA> ถนนจักรเพชร 157690710
62066 <NA> 6 yes <NA> <NA> <NA> ถนนราชดำเนินกลาง 24681047
62124 <NA> 6 yes <NA> <NA> <NA> ถนนราชดำเนินกลาง 134010893
62126 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินกลาง 156420649
62133 <NA> 6 yes <NA> <NA> <NA> ถนนราชดำเนินกลาง 162639456
62134 <NA> 3 yes <NA> <NA> <NA> ถนนราชดำเนินกลาง 162669720
62142 <NA> <NA> yes yes 1 <NA> ถนนราชดำเนินกลาง 169343042
62143 <NA> <NA> yes yes 1 <NA> ถนนราชดำเนินกลาง 169343049
62149 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินกลาง 175803676
62150 <NA> 3 yes yes 1 <NA> ถนนราชดำเนินนอก 176753955
osm_type Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF
10909 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62066 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62124 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62126 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62133 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62134 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62142 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62143 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62149 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
62150 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA>
ADM1ALT1EN ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE
10909 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62066 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62124 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62126 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62133 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62134 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62142 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62143 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62149 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
62150 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
date validOn validTo Shape_Leng.1 Shape_Area.1 ADM2_EN
10909 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62066 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62124 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62126 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62133 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62134 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62142 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62143 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62149 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
62150 2019-02-18 2022-01-22 <NA> 0.08541733 0.0004504685 Phra Nakhon
ADM2_TH ADM2_PCODE ADM2_REF ADM2ALT1EN ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH
10909 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62066 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62124 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62126 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62133 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62134 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62142 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62143 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62149 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
62150 พระนคร TH1001 <NA> <NA> <NA> <NA> <NA>
ADM1_EN.1 ADM1_TH.1 ADM1_PCODE.1 ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1
10909 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62066 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62124 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62126 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62133 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62134 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62142 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62143 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62149 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
62150 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
date.1 validOn.1 validTo.1 geometry
10909 2019-02-18 2022-01-22 <NA> LINESTRING (100.4951 13.742...
62066 2019-02-18 2022-01-22 <NA> LINESTRING (100.5022 13.756...
62124 2019-02-18 2022-01-22 <NA> LINESTRING (100.5015 13.756...
62126 2019-02-18 2022-01-22 <NA> LINESTRING (100.505 13.7561...
62133 2019-02-18 2022-01-22 <NA> LINESTRING (100.5052 13.755...
62134 2019-02-18 2022-01-22 <NA> LINESTRING (100.4952 13.757...
62142 2019-02-18 2022-01-22 <NA> LINESTRING (100.5058 13.756...
62143 2019-02-18 2022-01-22 <NA> LINESTRING (100.5055 13.756...
62149 2019-02-18 2022-01-22 <NA> LINESTRING (100.4949 13.757...
62150 2019-02-18 2022-01-22 <NA> LINESTRING (100.5091 13.763...city-data：
# Step 1: 从 bmr_city 中分别筛选出 Bangkok 和 Samut Prakan 的数据
bangkok_boundary <- bmr_city %>%
filter(ADM1_EN == "Bangkok")
SamutPrakan_boundary <- bmr_city %>%
filter(ADM1_EN == "Samut Prakan")3.acc-data：
bangkok_acc_data <- bmr_acc %>%
filter(province_en == "bangkok")
SamutPrakan_acc_data <- bmr_acc %>%
filter(province_en == "samut prakan")4.linestring：
# 确定目标坐标系为 UTM Zone 47N (EPSG: 32647)
target_crs <- 32647 # UTM Zone 47N
# 将事故数据和道路数据转换为 UTM 坐标系
bangkok_acc_data <- st_transform(bangkok_acc_data, crs = target_crs)
bangkok_roads_intersection <- st_transform(bangkok_roads_intersection, crs = target_crs)
bangkok_boundary <- st_transform(bangkok_boundary, crs = target_crs)
# 执行空间相交操作（剪切）
acc_in_bangkok <- st_intersection(bangkok_acc_data, bangkok_boundary)
roads_in_bangkok <- st_intersection(bangkok_roads_intersection, bangkok_boundary)
# 过滤出 LINESTRING 和 MULTILINESTRING 类型的几何对象
roads_in_bangkok <- roads_in_bangkok %>%
filter(st_geometry_type(roads_in_bangkok) %in% c("LINESTRING", "MULTILINESTRING"))
# 将 MULTILINESTRING 转换为多个 LINESTRING，保留所有线段
roads_in_bangkok <- st_cast(roads_in_bangkok, "LINESTRING", group_or_split = TRUE)
# 检查转换成功与否，应该显示为 LINESTRING
st_geometry_type(roads_in_bangkok) [1] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[7] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[13] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[19] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[25] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[31] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[37] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[43] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[49] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[55] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[61] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[67] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[73] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[79] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[85] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[91] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[97] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[103] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[109] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[115] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[121] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[127] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[133] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[139] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[145] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[151] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[157] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[163] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[169] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[175] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[181] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[187] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[193] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[199] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[205] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[211] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[217] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[223] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[229] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[235] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[241] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[247] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[253] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[259] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[265] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[271] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[277] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[283] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[289] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[295] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[301] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[307] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[313] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[319] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[325] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[331] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[337] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[343] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[349] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[355] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[361] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[367] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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18 Levels: GEOMETRY POINT LINESTRING POLYGON MULTIPOINT ... TRIANGLE# 确定目标坐标系为 UTM Zone 47N (EPSG: 32647)
target_crs <- 32647 # UTM Zone 47N
# 将事故数据和道路数据转换为 UTM 坐标系
SamutPrakan_acc_data <- st_transform(SamutPrakan_acc_data, crs = target_crs)
SamutPrakan_roads_intersection <- st_transform(SamutPrakan_roads_intersection, crs = target_crs)
SamutPrakan_boundary <- st_transform(SamutPrakan_boundary, crs = target_crs)
# 执行空间相交操作（剪切）
acc_in_SamutPrakan <- st_intersection(SamutPrakan_acc_data, SamutPrakan_boundary)
roads_in_SamutPrakan <- st_intersection(SamutPrakan_roads_intersection, SamutPrakan_boundary)
# 过滤出 LINESTRING 和 MULTILINESTRING 类型的几何对象
roads_in_SamutPrakan <- roads_in_SamutPrakan %>%
filter(st_geometry_type(roads_in_SamutPrakan) %in% c("LINESTRING", "MULTILINESTRING"))
# 将 MULTILINESTRING 转换为多个 LINESTRING，保留所有线段
roads_in_SamutPrakan <- st_cast(roads_in_SamutPrakan, "LINESTRING", group_or_split = TRUE)
# 检查转换成功与否，应该显示为 LINESTRING
st_geometry_type(roads_in_SamutPrakan) [1] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[7] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[13] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[19] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[25] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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18 Levels: GEOMETRY POINT LINESTRING POLYGON MULTIPOINT ... TRIANGLE5.acc_in_xx(city)：
# 将所有数据转换为UTM坐标系 (EPSG: 32647)
target_crs <- 32647 # UTM Zone 47N
# 转换事故数据和边界数据的CRS
bmr_acc_data <- st_transform(bmr_acc, crs = target_crs)
bmr_boundary <- st_transform(bmr, crs = target_crs)
# 执行剪切操作，获取BMR内的事故点
acc_in_bmr <- st_intersection(bmr_acc_data, bmr_boundary)
# 将 _roads_intersection 转换为 LINESTRING
roads_in_bangkok_lines <- st_cast(roads_in_bangkok, "LINESTRING")
roads_in_SamutPrakan_lines <- st_cast(roads_in_SamutPrakan, "LINESTRING")# 使用 lixelize_lines 函数生成 lixels，设置合适的单元长度
# 假设高速公路路段较长，选择 5000 米的 lixel 单元
lixels_bangkok <- lixelize_lines(roads_in_bangkok_lines,
10000, # 5000 米的 lixel 单元
mindist = 5000) # 最小距离设置为 5000 米
# 使用 lines_center 生成样本点，取每个 lixel 的中心点
samples_bangkok <- lines_center(lixels_bangkok)roads_in_SamutPrakan_lines <- st_cast(SamutPrakan_roads_intersection, "LINESTRING")
# 使用 lixelize_lines 函数生成 lixels，设置合适的单元长度
# 假设高速公路路段较长，选择 10000 米的 lixel 单元
lixels_SamutPrakan <- lixelize_lines(roads_in_SamutPrakan_lines,
10000, # 10000 米的 lixel 单元
mindist = 5000) # 最小距离设置为 5000 米
# 使用 lines_center 生成样本点，取每个 lixel 的中心点
samples_SamutPrakan <- lines_center(lixels_SamutPrakan)6.NEKD:
# 修改后的 nkde 函数，使用 bangkok 的数据
# Ensure acc_in_bangkok is an sf object with valid geometries
acc_in_bangkok <- st_as_sf(bangkok_acc_data)
# Same for Samut Prakan
acc_in_SamutPrakan <- st_as_sf(SamutPrakan_acc_data)
nkde_result_bangkok <- nkde(
lines = lixels_bangkok, # 替换为 Bangkok 的 lixels
events = acc_in_bangkok, # 替换为 Bangkok 的事故数据
w = rep(1, nrow(acc_in_bangkok)), # 权重
samples = samples_bangkok, # 使用 samples_bangkok
kernel_name = "quartic", # 四次核
bw = 500, # 带宽为500米
div = "bw", # 带宽标准化
method = "simple", # 简单方法
grid_shape = c(200, 200), # 网格形状
verbose = TRUE # 打印详细信息
)[1] "checking inputs ..."
[1] "prior data preparation ..."
[1] "Splitting the data with the spatial grid ..."
[1] "start calculating the kernel values ..."
[1] " quadra 1/2683"
[1] " quadra 2/2683"
[1] " quadra 3/2683"
[1] " quadra 4/2683"
[1] " quadra 5/2683"
[1] " quadra 6/2683"
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[1] "combining the results ..."# 修改后的 nkde 函数，使用 Samut_Prakan 的数据
nkde_result_SamutPrakan <- nkde(
lines = lixels_SamutPrakan, # 替换为 Samut_Prakan 的 lixels
events = acc_in_SamutPrakan, # 替换为 Samut_Prakan 的事故数据
w = rep(1, nrow(acc_in_SamutPrakan)), # 权重
samples = samples_SamutPrakan, # 使用 samples_Samut_Prakan
kernel_name = "quartic", # 四次核
bw = 500, # 带宽为500米
div = "bw", # 带宽标准化
method = "simple", # 简单方法
grid_shape = c(200, 200), # 网格形状
verbose = TRUE # 打印详细信息
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[1] "combining the results ..."7.diffent：
print(nkde_result_bangkok) [1] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[6] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[11] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[16] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[21] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[26] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[31] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[36] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[41] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[46] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[51] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[56] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[61] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[66] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[71] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[76] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[81] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[86] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[91] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[96] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[156] 0.000000e+00 0.000000e+00 1.797126e-06 0.000000e+00 0.000000e+00
[161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[171] 0.000000e+00 1.696405e-08 0.000000e+00 0.000000e+00 0.000000e+00
[176] 0.000000e+00 0.000000e+00 0.000000e+00 1.398770e-07 0.000000e+00
[181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[186] 0.000000e+00 4.685121e-07 0.000000e+00 0.000000e+00 0.000000e+00
[191] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 3.737865e-07
[196] 5.920879e-07 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[201] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[206] 9.116359e-07 1.990933e-06 1.059222e-06 0.000000e+00 0.000000e+00
[211] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[216] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[221] 0.000000e+00 0.000000e+00 0.000000e+00 1.297769e-08 0.000000e+00
[226] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[231] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[236] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 6.656817e-08
[241] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[246] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[251] 0.000000e+00 0.000000e+00 2.382190e-08 5.320467e-08 2.359191e-06
[256] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[261] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[266] 7.025007e-08 0.000000e+00 0.000000e+00 0.000000e+00 1.390769e-06
[271] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[276] 0.000000e+00 0.000000e+00 1.844973e-06 0.000000e+00 1.215640e-05
[281] 0.000000e+00 7.024518e-06 1.799427e-06 1.641238e-05 5.239336e-06
[286] 2.199947e-06 0.000000e+00 0.000000e+00 7.156931e-07 3.555842e-06
[291] 0.000000e+00 6.646976e-06 2.356076e-05 3.492516e-06 0.000000e+00
[296] 0.000000e+00 5.614937e-06 1.867668e-06 9.251491e-06 1.868636e-05
[301] 0.000000e+00 9.213527e-08 1.344169e-06 0.000000e+00 3.299578e-06
[306] 0.000000e+00 1.389824e-05 0.000000e+00 0.000000e+00 0.000000e+00
[311] 0.000000e+00 2.434135e-06 3.624873e-07 0.000000e+00 3.055711e-06
[316] 0.000000e+00 3.248931e-07 0.000000e+00 1.266403e-05 1.922768e-06
[321] 3.946660e-08 2.378681e-06 0.000000e+00 0.000000e+00 9.718579e-06
[326] 0.000000e+00 1.090929e-05 0.000000e+00 0.000000e+00 0.000000e+00
[331] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7.298704e-06
[336] 0.000000e+00 1.100718e-05 7.133622e-06 0.000000e+00 0.000000e+00
[341] 0.000000e+00 4.954428e-06 0.000000e+00 0.000000e+00 0.000000e+00
[346] 2.223315e-07 0.000000e+00 0.000000e+00 1.637442e-06 1.074396e-05
[351] 3.722528e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[356] 0.000000e+00 0.000000e+00 0.000000e+00 5.983345e-06 0.000000e+00
[361] 3.670767e-06 0.000000e+00 0.000000e+00 1.067183e-05 0.000000e+00
[366] 1.019622e-05 1.711697e-06 2.435058e-06 0.000000e+00 3.374460e-08
[371] 0.000000e+00 0.000000e+00 3.073637e-06 6.372753e-06 3.465985e-06
[376] 9.062190e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[381] 7.388782e-06 2.719025e-06 3.426102e-06 7.323033e-06 6.370424e-06
[386] 2.153409e-06 7.407200e-06 9.338092e-07 2.019150e-06 8.808200e-06
[391] 9.144903e-06 9.093062e-06 2.946735e-06 1.015799e-05 1.060599e-05
[396] 0.000000e+00 1.930928e-05 6.586580e-06 0.000000e+00 0.000000e+00
[401] 8.706537e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[406] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[411] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 6.780502e-06
[416] 1.572883e-05 0.000000e+00 4.614672e-06 0.000000e+00 0.000000e+00
[421] 6.335798e-06 0.000000e+00 0.000000e+00 0.000000e+00 6.078484e-06
[426] 1.144708e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[431] 0.000000e+00 0.000000e+00 9.084216e-06 3.445999e-06 1.665765e-06
[436] 1.584454e-06 7.953323e-07 6.530353e-06 6.211192e-06 0.000000e+00
[441] 1.259346e-05 0.000000e+00 0.000000e+00 1.254062e-05 0.000000e+00
[446] 1.255742e-05 1.246927e-05 0.000000e+00 6.234456e-06 1.230884e-05
[451] 0.000000e+00 1.158821e-05 1.745471e-08 7.693164e-06 5.127248e-06
[456] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[461] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[466] 0.000000e+00 0.000000e+00 0.000000e+00 3.779482e-06 2.658069e-06
[471] 9.930298e-07 3.249750e-06 4.353202e-09 3.285916e-06 3.068102e-06
[476] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.915223e-07
[481] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[486] 1.009233e-06 7.833319e-07 0.000000e+00 0.000000e+00 0.000000e+00
[491] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[496] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[501] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[506] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[511] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[516] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[521] 0.000000e+00 0.000000e+00 0.000000e+00 1.488694e-06 0.000000e+00
[526] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[531] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[536] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[541] 7.329366e-07 0.000000e+00 0.000000e+00 0.000000e+00 5.916741e-06
[546] 0.000000e+00 6.009681e-06 0.000000e+00 0.000000e+00 0.000000e+00
[551] 0.000000e+00 0.000000e+00 0.000000e+00 5.924518e-07 0.000000e+00
[556] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[561] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[566] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[571] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[576] 5.567481e-07 2.885810e-09 0.000000e+00 0.000000e+00 0.000000e+00
[581] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[586] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[591] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[596] 0.000000e+00 6.820765e-05 1.033993e-05 7.485733e-08 0.000000e+00
[601] 0.000000e+00 0.000000e+00 1.495734e-07 3.454084e-06 1.250815e-06
[606] 0.000000e+00 0.000000e+00 3.237794e-06 0.000000e+00 0.000000e+00
[611] 0.000000e+00 6.807831e-05 0.000000e+00 0.000000e+00 0.000000e+00
[616] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[621] 0.000000e+00 0.000000e+00 0.000000e+00 1.855260e-06 0.000000e+00
[626] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[631] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[636] 0.000000e+00 0.000000e+00 0.000000e+00 5.280103e-10 2.096844e-06
[641] 3.082500e-06 3.561545e-06 6.582888e-06 0.000000e+00 0.000000e+00
[646] 0.000000e+00 0.000000e+00 7.170204e-06 6.214629e-06 0.000000e+00
[651] 6.046492e-06 3.775188e-06 0.000000e+00 0.000000e+00 0.000000e+00
[656] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[661] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[666] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.919334e-06
[671] 5.377777e-06 4.761273e-08 0.000000e+00 0.000000e+00 3.929693e-07
[676] 8.003699e-09 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[681] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[686] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[691] 0.000000e+00 0.000000e+00 3.190769e-06 0.000000e+00 0.000000e+00
[696] 5.557049e-07 1.619271e-07 0.000000e+00 0.000000e+00 0.000000e+00
[701] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.089955e-06
[706] 3.560875e-06 0.000000e+00 1.398111e-06 0.000000e+00 0.000000e+00
[711] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[716] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[721] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[726] 0.000000e+00 0.000000e+00 0.000000e+00 2.242244e-06 0.000000e+00
[731] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[736] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[741] 0.000000e+00 8.332891e-10 0.000000e+00 0.000000e+00 0.000000e+00
[746] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
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[8141] 5.622937e-08 1.407816e-06 3.557150e-05 1.735692e-05 1.221713e-05
[8146] 4.239765e-05 3.723431e-06 2.995026e-06 9.083668e-06 8.299504e-06
[8151] 0.000000e+00 3.707245e-06 0.000000e+00 3.921318e-06 3.420578e-06
[8156] 1.500046e-06 8.823863e-06 9.538738e-06 2.067911e-11 5.509232e-06
[8161] 8.934613e-07 7.998770e-06 2.052893e-06 0.000000e+00 0.000000e+00
[8166] 3.545413e-09 0.000000e+00 1.471538e-06 0.000000e+00 1.688827e-07
[8171] 6.250759e-07 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8176] 0.000000e+00 3.547794e-06 3.121255e-06 3.395192e-06 5.866686e-06
[8181] 2.817802e-05 5.165158e-06 5.932717e-06 4.522805e-06 6.902157e-06
[8186] 6.370953e-06 4.911931e-06 1.395148e-06 3.408752e-05 9.027555e-08
[8191] 0.000000e+00 2.585596e-06 5.954561e-06 3.405405e-06 3.477568e-06
[8196] 3.730651e-06 9.396041e-06 3.896569e-05 3.371143e-05 0.000000e+00
[8201] 0.000000e+00 5.748356e-06 0.000000e+00 3.900597e-05 6.584342e-05
[8206] 0.000000e+00 0.000000e+00 2.841007e-06 0.000000e+00 4.689411e-07
[8211] 0.000000e+00 2.575797e-06 0.000000e+00 0.000000e+00 3.735532e-06
[8216] 2.907127e-06 3.497219e-06 5.932816e-06 2.390238e-06 3.566799e-06
[8221] 0.000000e+00 3.218440e-06 3.472711e-06 3.741152e-06 2.126720e-06
[8226] 3.318464e-06 3.656159e-06 7.932668e-05 5.559753e-05 6.133550e-07
[8231] 5.481608e-05 4.906377e-05 2.739196e-05 1.737475e-05 2.271676e-06
[8236] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8241] 0.000000e+00 4.954285e-05 3.085940e-05 4.746320e-05 5.932971e-07
[8246] 1.401494e-05 2.698599e-05 1.193305e-05 2.431692e-05 0.000000e+00
[8251] 0.000000e+00 0.000000e+00 1.681705e-05 1.319389e-05 0.000000e+00
[8256] 0.000000e+00 9.363398e-06 0.000000e+00 5.761816e-06 2.505584e-08
[8261] 0.000000e+00 0.000000e+00 0.000000e+00 5.715421e-06 0.000000e+00
[8266] 0.000000e+00 4.080276e-05 0.000000e+00 5.337731e-05 0.000000e+00
[8271] 0.000000e+00 3.049195e-05 0.000000e+00 0.000000e+00 0.000000e+00
[8276] 0.000000e+00 0.000000e+00 6.919050e-05 3.144213e-05 0.000000e+00
[8281] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 6.040828e-07
[8286] 5.257493e-05 0.000000e+00 7.844999e-05 0.000000e+00 0.000000e+00
[8291] 0.000000e+00 0.000000e+00 2.485375e-05 0.000000e+00 3.077351e-05
[8296] 2.142905e-05 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8301] 0.000000e+00 2.585523e-05 0.000000e+00 0.000000e+00 0.000000e+00
[8306] 0.000000e+00 0.000000e+00 3.314401e-05 0.000000e+00 0.000000e+00
[8311] 4.829689e-05 0.000000e+00 9.255183e-05 2.214616e-05 0.000000e+00
[8316] 0.000000e+00 1.945312e-06 0.000000e+00 0.000000e+00 3.838184e-05
[8321] 2.586279e-06 3.345406e-06 1.118715e-05 6.770065e-05 0.000000e+00
[8326] 8.682265e-05 8.100575e-05 0.000000e+00 0.000000e+00 0.000000e+00
[8331] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7.126444e-05
[8336] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 5.201893e-05
[8341] 0.000000e+00 0.000000e+00 0.000000e+00 5.928725e-05 0.000000e+00
[8346] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8351] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8356] 0.000000e+00 0.000000e+00 0.000000e+00 7.435298e-05 1.187922e-04
[8361] 7.070859e-05 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8366] 0.000000e+00 0.000000e+00 5.851578e-05 2.146416e-05 6.642241e-05
[8371] 4.405376e-05 8.782761e-05 2.524028e-05 4.496796e-05 4.209299e-06
[8376] 4.618405e-05 1.050484e-05 0.000000e+00 0.000000e+00 1.927560e-06
[8381] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8386] 0.000000e+00 3.863099e-06 4.857098e-07 6.743030e-06 2.188818e-06
[8391] 0.000000e+00 0.000000e+00 9.471619e-07 0.000000e+00 0.000000e+00
[8396] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8401] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8406] 0.000000e+00 1.565508e-06 3.551597e-07 0.000000e+00 0.000000e+00
[8411] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8416] 9.436570e-07 8.920523e-06 2.158941e-05 0.000000e+00 0.000000e+00
[8421] 0.000000e+00 0.000000e+00 1.513487e-07 3.699833e-06 3.444521e-06
[8426] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8431] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8436] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8441] 2.275497e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8446] 0.000000e+00 0.000000e+00 0.000000e+00 5.042667e-06 0.000000e+00
[8451] 0.000000e+00 0.000000e+00 1.743764e-05 1.483369e-05 1.981239e-05
[8456] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8461] 0.000000e+00 0.000000e+00 3.848588e-06 0.000000e+00 1.894890e-08
[8466] 9.294303e-05 2.554583e-05 3.689934e-06 1.595374e-05 1.047759e-06
[8471] 1.770698e-06 6.227060e-05 6.406819e-05 0.000000e+00 3.564915e-06
[8476] 2.684943e-05 0.000000e+00 3.714297e-06 0.000000e+00 0.000000e+00
[8481] 0.000000e+00 0.000000e+00 3.912012e-06 3.744292e-06 3.774659e-06
[8486] 0.000000e+00 0.000000e+00 3.737110e-06 0.000000e+00 1.479300e-05
[8491] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8496] 4.471124e-05 9.121258e-05 0.000000e+00 0.000000e+00 6.451393e-07
[8501] 1.490501e-05 3.147298e-06 2.668112e-06 3.592691e-06 1.072063e-06
[8506] 1.790186e-06 4.055031e-06 3.891474e-06 5.562215e-05 5.876068e-05
[8511] 1.725621e-05 6.295634e-05 0.000000e+00 1.867844e-06 8.690472e-08
[8516] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7.911483e-05
[8521] 9.191417e-05 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8526] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8531] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8536] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8541] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8546] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8551] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8556] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8561] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 6.097539e-05
[8566] 7.471108e-05 3.287382e-05 6.997943e-05 0.000000e+00 0.000000e+00
[8571] 3.567600e-06 3.476111e-06 0.000000e+00 0.000000e+00 0.000000e+00
[8576] 0.000000e+00 3.753775e-06 4.028963e-06 3.572963e-06 0.000000e+00
[8581] 4.013092e-06 0.000000e+00 2.383499e-06 2.906416e-06 3.564890e-06
[8586] 3.655618e-06 2.028381e-05 2.438617e-05 2.557073e-05 0.000000e+00
[8591] 0.000000e+00 0.000000e+00 1.904936e-06 0.000000e+00 0.000000e+00
[8596] 4.398184e-06 6.816438e-06 1.054615e-05 0.000000e+00 0.000000e+00
[8601] 1.074873e-05 4.455011e-06 0.000000e+00 1.636376e-06 1.096589e-05
[8606] 1.101135e-05 2.283312e-06 0.000000e+00 9.186485e-06 0.000000e+00
[8611] 0.000000e+00 3.716736e-07 0.000000e+00 3.747102e-06 0.000000e+00
[8616] 0.000000e+00 8.737410e-07 0.000000e+00 1.118613e-06 7.225470e-06
[8621] 3.170229e-06 0.000000e+00 4.474725e-06 0.000000e+00 2.225297e-06
[8626] 9.797420e-06 0.000000e+00 7.219608e-06 0.000000e+00 0.000000e+00
[8631] 9.687151e-06 0.000000e+00 1.059722e-05 1.040693e-05 3.306354e-06
[8636] 0.000000e+00 0.000000e+00 0.000000e+00 1.080820e-05 1.090724e-05
[8641] 0.000000e+00 1.097113e-05 9.706480e-06 1.418083e-06 7.812167e-06
[8646] 4.426855e-06 0.000000e+00 1.674656e-06 0.000000e+00 1.019012e-05
[8651] 8.267139e-06 2.314400e-06 6.398638e-06 1.051968e-05 9.991298e-07
[8656] 1.850746e-06 1.381101e-05 1.990430e-08 2.598420e-06 1.389506e-05
[8661] 1.324620e-05 1.592950e-06 7.700684e-08 1.184894e-05 0.000000e+00
[8666] 0.000000e+00 6.824838e-06 2.179077e-05 6.226569e-07 8.226244e-06
[8671] 7.520647e-06 9.108485e-06 7.040842e-06 4.478783e-06 6.086479e-06
[8676] 5.405308e-06 5.957211e-06 1.531749e-08 0.000000e+00 0.000000e+00
[8681] 0.000000e+00 3.177729e-06 9.463065e-06 3.743189e-06 1.906311e-06
[8686] 0.000000e+00 0.000000e+00 3.701244e-07 0.000000e+00 8.589808e-07
[8691] 3.558210e-08 0.000000e+00 2.460619e-06 0.000000e+00 1.058811e-05
[8696] 1.096439e-05 0.000000e+00 8.432396e-09 8.390006e-06 2.394743e-06
[8701] 6.150134e-06 1.080279e-05 1.079060e-05 0.000000e+00 0.000000e+00
[8706] 1.098536e-05 1.001982e-05 0.000000e+00 0.000000e+00 0.000000e+00
[8711] 0.000000e+00 7.603336e-06 0.000000e+00 0.000000e+00 0.000000e+00
[8716] 0.000000e+00 1.845554e-07 0.000000e+00 8.447551e-06 4.703291e-06
[8721] 2.862921e-06 0.000000e+00 5.940954e-06 0.000000e+00 0.000000e+00
[8726] 0.000000e+00 2.498991e-06 0.000000e+00 1.884281e-05 0.000000e+00
[8731] 0.000000e+00 2.688118e-05 1.130235e-05 3.435324e-05 7.207937e-06
[8736] 3.139727e-05 3.282322e-06 9.444378e-05 6.508949e-05 1.865195e-05
[8741] 0.000000e+00 1.286764e-05 1.426418e-05 0.000000e+00 4.452011e-05
[8746] 9.146127e-06 5.873450e-06 0.000000e+00 2.798857e-06 3.354321e-06
[8751] 1.488465e-04 1.433597e-05 3.736745e-06 7.188073e-06 1.278793e-05
[8756] 6.510202e-06 1.148289e-05 0.000000e+00 0.000000e+00 0.000000e+00
[8761] 0.000000e+00 1.152996e-06 4.577598e-07 1.920014e-05 0.000000e+00
[8766] 3.718161e-05 1.572644e-05 0.000000e+00 0.000000e+00 5.600286e-05
[8771] 2.141338e-06 6.088608e-05 2.167417e-05 0.000000e+00 0.000000e+00
[8776] 0.000000e+00 1.369219e-05 8.598171e-06 1.162441e-05 1.048046e-05
[8781] 0.000000e+00 1.138323e-06 3.978157e-05 0.000000e+00 0.000000e+00
[8786] 0.000000e+00 0.000000e+00 1.488712e-05 6.608242e-05 4.831961e-05
[8791] 4.330620e-05 9.959006e-05 1.185613e-05 2.325748e-05 2.119917e-05
[8796] 2.526570e-05 9.331445e-06 0.000000e+00 0.000000e+00 0.000000e+00
[8801] 0.000000e+00 0.000000e+00 0.000000e+00 1.673496e-05 1.003716e-05
[8806] 0.000000e+00 0.000000e+00 2.475385e-07 1.450685e-05 4.526178e-05
[8811] 2.602282e-05 0.000000e+00 0.000000e+00 4.548532e-07 1.702690e-05
[8816] 6.770124e-06 5.575047e-05 0.000000e+00 1.569470e-06 5.446758e-05
[8821] 3.917894e-05 1.168075e-05 3.693003e-05 3.124254e-05 1.885765e-05
[8826] 9.337287e-06 3.972367e-05 0.000000e+00 0.000000e+00 0.000000e+00
[8831] 1.335809e-05 8.925014e-06 0.000000e+00 1.148387e-05 0.000000e+00
[8836] 1.517157e-05 0.000000e+00 2.972327e-05 7.223287e-05 3.724073e-06
[8841] 4.905142e-05 8.599100e-06 2.235346e-05 1.435608e-05 1.956901e-05
[8846] 5.549304e-05 3.089834e-05 0.000000e+00 0.000000e+00 0.000000e+00
[8851] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.128183e-05
[8856] 5.964240e-07 5.642427e-06 1.977589e-05 9.572121e-06 0.000000e+00
[8861] 2.424610e-05 0.000000e+00 0.000000e+00 0.000000e+00 1.501823e-05
[8866] 1.112974e-05 1.362985e-05 2.326184e-06 1.652137e-05 0.000000e+00
[8871] 6.099422e-05 0.000000e+00 4.171912e-05 8.561950e-05 1.483146e-05
[8876] 1.521746e-05 7.437307e-05 2.780350e-05 2.548277e-05 3.739935e-05
[8881] 5.438291e-06 1.259697e-05 1.465208e-05 6.137254e-06 1.113577e-05
[8886] 9.396119e-06 3.632872e-06 1.070051e-05 1.480068e-05 2.181409e-05
[8891] 2.333744e-05 2.453683e-05 1.581673e-05 1.883705e-05 4.360252e-05
[8896] 4.190093e-05 3.856703e-06 8.838088e-05 1.399614e-04 0.000000e+00
[8901] 0.000000e+00 0.000000e+00 0.000000e+00 2.904723e-06 0.000000e+00
[8906] 1.587114e-05 0.000000e+00 1.487018e-05 0.000000e+00 0.000000e+00
[8911] 0.000000e+00 1.956536e-05 9.793531e-06 2.088706e-06 1.888650e-06
[8916] 9.940963e-06 3.740264e-05 2.616738e-05 3.079246e-05 9.182881e-06
[8921] 0.000000e+00 0.000000e+00 0.000000e+00 7.518509e-06 3.743234e-06
[8926] 5.840700e-06 1.179798e-05 1.402502e-05 1.409108e-06 7.696941e-06
[8931] 9.003097e-06 1.034810e-05 1.528439e-05 0.000000e+00 0.000000e+00
[8936] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8941] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8946] 2.624682e-05 0.000000e+00 1.099077e-05 9.506880e-06 0.000000e+00
[8951] 1.137894e-05 3.516567e-05 1.433558e-05 0.000000e+00 0.000000e+00
[8956] 1.379068e-05 8.650746e-06 0.000000e+00 0.000000e+00 0.000000e+00
[8961] 3.743000e-06 0.000000e+00 0.000000e+00 0.000000e+00 8.364188e-05
[8966] 5.229016e-08 7.599961e-06 0.000000e+00 0.000000e+00 0.000000e+00
[8971] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8976] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8981] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8986] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8991] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[8996] 0.000000e+00 0.000000e+00 0.000000e+00 3.538543e-06 0.000000e+00
[9001] 0.000000e+00 0.000000e+00 0.000000e+00 3.648946e-06 1.193370e-05
[9006] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9011] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9016] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9021] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9026] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9031] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.420944e-05
[9036] 1.389582e-09 3.683050e-05 2.085348e-05 0.000000e+00 0.000000e+00
[9041] 1.640418e-05 9.385660e-06 9.066886e-06 0.000000e+00 0.000000e+00
[9046] 1.212919e-05 6.153039e-06 8.204537e-06 1.251473e-05 2.117006e-05
[9051] 2.343564e-05 0.000000e+00 0.000000e+00 5.296602e-06 0.000000e+00
[9056] 0.000000e+00 5.668664e-06 0.000000e+00 0.000000e+00 1.087549e-05
[9061] 5.311981e-06 1.330456e-05 7.230244e-06 1.267972e-05 0.000000e+00
[9066] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9071] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9076] 1.417702e-07 1.169280e-06 3.891322e-06 2.280142e-06 0.000000e+00
[9081] 6.744273e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9086] 0.000000e+00 0.000000e+00 8.722272e-06 0.000000e+00 9.256178e-06
[9091] 8.144799e-06 6.795240e-06 8.999001e-06 1.070536e-05 0.000000e+00
[9096] 1.027576e-05 1.576335e-05 0.000000e+00 0.000000e+00 0.000000e+00
[9101] 1.360471e-05 1.425764e-05 1.265967e-05 6.837101e-06 7.175901e-06
[9106] 0.000000e+00 0.000000e+00 6.115519e-06 0.000000e+00 4.280826e-06
[9111] 3.517401e-06 2.034884e-06 5.024481e-06 4.286403e-06 1.891131e-05
[9116] 2.942515e-06 0.000000e+00 2.204166e-05 0.000000e+00 0.000000e+00
[9121] 2.858436e-06 0.000000e+00 3.331110e-06 1.886007e-06 0.000000e+00
[9126] 0.000000e+00 3.767866e-06 3.437492e-06 1.948246e-06 9.555560e-06
[9131] 3.517121e-05 4.783468e-06 1.059869e-09 1.899528e-05 3.204048e-06
[9136] 2.962181e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9141] 7.411923e-06 6.911184e-06 1.480042e-05 8.658562e-07print(nkde_result_SamutPrakan) [1] 0.000000e+00 0.000000e+00 0.000000e+00 3.494534e-06 3.262701e-06
[6] 2.948858e-06 2.069294e-06 3.461549e-06 0.000000e+00 0.000000e+00
[11] 5.726079e-06 0.000000e+00 3.492638e-06 6.663774e-06 3.668699e-06
[16] 4.108230e-05 0.000000e+00 0.000000e+00 0.000000e+00 2.286119e-06
[21] 3.168831e-06 6.656313e-06 0.000000e+00 0.000000e+00 9.465650e-08
[26] 0.000000e+00 0.000000e+00 9.731011e-08 3.221850e-06 3.124893e-06
[31] 3.576321e-06 2.348798e-06 3.759297e-07 3.442695e-06 4.666151e-06
[36] 2.030863e-06 2.687329e-06 0.000000e+00 0.000000e+00 0.000000e+00
[41] 0.000000e+00 0.000000e+00 1.174681e-06 2.490459e-06 1.161145e-06
[46] 4.826543e-06 3.632957e-06 3.423648e-06 0.000000e+00 1.180858e-11
[51] 5.517015e-06 2.435184e-06 8.914182e-07 0.000000e+00 8.065636e-06
[56] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.558657e-06
[61] 0.000000e+00 3.444098e-06 4.228264e-06 0.000000e+00 0.000000e+00
[66] 3.256330e-06 1.121763e-06 0.000000e+00 3.566858e-06 3.127851e-06
[71] 0.000000e+00 2.150030e-07 0.000000e+00 0.000000e+00 6.480558e-06
[76] 6.563965e-06 9.617832e-10 7.307140e-06 0.000000e+00 0.000000e+00
[81] 0.000000e+00 4.230536e-06 5.511411e-06 7.273726e-08 0.000000e+00
[86] 8.294441e-06 7.285718e-06 2.875834e-06 0.000000e+00 3.674417e-06
[91] 0.000000e+00 0.000000e+00 0.000000e+00 7.184544e-06 0.000000e+00
[96] 4.411567e-06 4.279312e-06 3.981295e-06 4.282008e-06 3.420327e-06
[101] 3.178083e-06 6.705535e-06 0.000000e+00 3.139886e-06 3.534342e-06
[106] 4.920463e-07 2.335402e-06 3.067592e-06 4.073988e-07 2.842882e-06
[111] 0.000000e+00 1.277515e-06 9.592650e-06 6.220365e-06 5.277144e-06
[116] 0.000000e+00 0.000000e+00 3.595329e-06 0.000000e+00 0.000000e+00
[121] 0.000000e+00 0.000000e+00 1.208943e-05 0.000000e+00 7.681290e-06
[126] 7.258255e-06 0.000000e+00 7.352862e-06 0.000000e+00 0.000000e+00
[131] 0.000000e+00 3.743802e-06 0.000000e+00 0.000000e+00 0.000000e+00
[136] 3.671983e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[141] 0.000000e+00 0.000000e+00 0.000000e+00 1.269115e-06 0.000000e+00
[146] 1.459079e-05 0.000000e+00 3.627635e-05 2.578938e-05 0.000000e+00
[151] 0.000000e+00 2.245853e-06 2.333341e-06 0.000000e+00 0.000000e+00
[156] 9.052157e-07 0.000000e+00 5.987898e-07 3.265880e-06 0.000000e+00
[161] 1.083135e-06 1.123653e-06 0.000000e+00 0.000000e+00 0.000000e+00
[166] 0.000000e+00 0.000000e+00 0.000000e+00 5.610442e-06 0.000000e+00
[171] 3.750234e-07 0.000000e+00 0.000000e+00 2.923845e-06 6.402374e-07
[176] 0.000000e+00 0.000000e+00 2.637637e-06 0.000000e+00 6.449029e-07
[181] 4.804052e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[186] 2.731967e-06 1.947315e-06 0.000000e+00 0.000000e+00 0.000000e+00
[191] 1.921971e-06 3.801131e-06 2.738222e-06 0.000000e+00 3.570201e-06
[196] 8.482044e-07 0.000000e+00 4.814710e-06 0.000000e+00 0.000000e+00
[201] 0.000000e+00 0.000000e+00 7.092256e-06 0.000000e+00 0.000000e+00
[206] 8.674133e-06 0.000000e+00 3.088717e-07 6.240516e-06 9.602422e-07
[211] 2.696121e-06 9.468462e-06 0.000000e+00 2.473729e-05 8.102538e-06
[216] 5.995594e-06 4.746939e-06 2.838052e-06 3.359818e-06 5.814737e-06
[221] 9.220221e-06 3.818528e-06 1.319899e-05 0.000000e+00 3.499430e-06
[226] 0.000000e+00 2.047025e-06 7.739184e-07 3.431332e-06 3.747511e-06
[231] 3.483092e-06 3.130322e-06 0.000000e+00 0.000000e+00 1.382147e-06
[236] 7.447498e-06 2.238162e-07 4.037840e-06 0.000000e+00 5.929295e-07
[241] 3.007737e-06 3.999934e-06 3.852326e-06 0.000000e+00 0.000000e+00
[246] 0.000000e+00 4.499201e-06 3.576515e-06 3.399134e-06 0.000000e+00
[251] 6.476085e-06 3.686823e-06 0.000000e+00 0.000000e+00 0.000000e+00
[256] 6.233606e-06 0.000000e+00 6.051374e-06 2.298425e-06 1.069020e-07
[261] 8.355290e-06 7.023996e-06 0.000000e+00 3.711844e-06 5.611227e-07
[266] 3.238487e-06 5.422993e-06 0.000000e+00 0.000000e+00 2.247184e-08
[271] 0.000000e+00 6.706426e-06 0.000000e+00 0.000000e+00 3.720089e-06
[276] 5.196424e-06 5.838650e-06 5.925262e-06 0.000000e+00 3.745482e-06
[281] 1.424135e-05 8.454284e-07 3.746104e-06 2.847687e-06 4.311114e-06
[286] 4.452343e-06 0.000000e+00 1.586831e-06 4.707565e-06 1.535350e-05
[291] 1.580655e-05 0.000000e+00 1.289185e-05 1.093568e-05 0.000000e+00
[296] 1.134717e-05 7.445033e-06 8.448733e-06 9.179704e-06 9.408297e-06
[301] 5.854393e-06 3.499827e-06 2.183986e-06 0.000000e+00 0.000000e+00
[306] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7.419168e-06
[311] 5.389042e-06 5.543616e-06 0.000000e+00 8.569666e-06 1.819415e-06
[316] 0.000000e+00 0.000000e+00 0.000000e+00 1.018460e-07 5.587379e-06
[321] 1.614308e-06 0.000000e+00 2.875798e-07 1.147100e-06 1.134045e-06
[326] 5.288456e-06 0.000000e+00 0.000000e+00 0.000000e+00 6.717571e-06
[331] 4.714336e-06 4.898162e-06 4.001085e-06 3.809395e-06 2.417585e-06
[336] 0.000000e+00 0.000000e+00 7.465231e-07 0.000000e+00 0.000000e+00
[341] 0.000000e+00 4.310009e-06 0.000000e+00 0.000000e+00 3.103810e-07
[346] 6.003134e-06 8.481084e-06 2.039664e-06 0.000000e+00 0.000000e+00
[351] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 6.297348e-06
[356] 5.344752e-06 5.449236e-06 6.394525e-06 0.000000e+00 0.000000e+00
[361] 1.804078e-06 2.272740e-07 1.575570e-06 3.652927e-06 4.652332e-07
[366] 3.315563e-06 9.151185e-08 0.000000e+00 1.507705e-07 0.000000e+00
[371] 5.049896e-07 2.617310e-06 3.747122e-06 0.000000e+00 2.804361e-07
[376] 1.316967e-05 0.000000e+00 4.095777e-06 1.744995e-07 6.614536e-07
[381] 0.000000e+00 2.996084e-06 4.922320e-06 0.000000e+00 3.680902e-06
[386] 1.887262e-06 6.820870e-06 6.830986e-06 0.000000e+00 2.282778e-06
[391] 0.000000e+00 0.000000e+00 4.427298e-06 0.000000e+00 0.000000e+00
[396] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[401] 0.000000e+00 0.000000e+00 6.427039e-06 3.159816e-07 6.858883e-06
[406] 0.000000e+00 0.000000e+00 0.000000e+00 4.986552e-06 4.009652e-06
[411] 7.900738e-06 1.151431e-05 7.899001e-06 3.060353e-06 7.659357e-06
[416] 1.185251e-05 7.664300e-06 3.663332e-06 3.778535e-06 0.000000e+00
[421] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[426] 0.000000e+00 5.029650e-05 6.127620e-06 0.000000e+00 0.000000e+00
[431] 0.000000e+00 0.000000e+00 1.071772e-05 3.533885e-08 0.000000e+00
[436] 0.000000e+00 0.000000e+00 1.633037e-06 3.563971e-05 2.600764e-06
[441] 6.995623e-05 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[446] 0.000000e+00 6.891390e-06 4.351176e-07 0.000000e+00 0.000000e+00
[451] 3.658736e-06 2.398553e-06 0.000000e+00 1.874812e-05 2.111518e-09
[456] 0.000000e+00 2.350065e-06 3.155873e-06 2.744606e-06 0.000000e+00
[461] 3.738853e-06 4.315723e-07 0.000000e+00 6.948051e-07 0.000000e+00
[466] 7.926204e-06 7.050477e-06 0.000000e+00 3.339112e-06 0.000000e+00
[471] 3.509075e-06 0.000000e+00 0.000000e+00 3.678003e-06 2.033134e-06
[476] 0.000000e+00 4.124339e-06 0.000000e+00 3.596785e-06 1.463221e-06
[481] 7.777746e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[486] 0.000000e+00 2.087780e-09 7.498275e-06 4.357098e-06 9.925904e-09
[491] 3.322377e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[496] 1.068010e-04 3.564179e-06 0.000000e+00 0.000000e+00 0.000000e+00
[501] 0.000000e+00 3.036545e-06 0.000000e+00 4.495250e-07 1.813276e-06
[506] 0.000000e+00 2.257904e-05 0.000000e+00 2.037299e-05 0.000000e+00
[511] 3.331561e-06 0.000000e+00 4.507426e-06 8.225979e-07 6.817581e-06
[516] 3.036105e-06 0.000000e+00 1.312042e-06 0.000000e+00 0.000000e+00
[521] 0.000000e+00 0.000000e+00 0.000000e+00 6.517514e-06 2.785177e-06
[526] 0.000000e+00 7.499933e-06 0.000000e+00 0.000000e+00 0.000000e+00
[531] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7.209725e-06
[536] 7.378142e-06 6.994210e-06 1.097502e-06 0.000000e+00 0.000000e+00
[541] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[546] 4.802946e-07 0.000000e+00 3.594498e-06 0.000000e+00 0.000000e+00
[551] 0.000000e+00 3.701291e-06 0.000000e+00 0.000000e+00 0.000000e+00
[556] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 5.864276e-06
[561] 5.533233e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[566] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 5.876303e-06
[571] 8.963951e-06 3.761177e-06 1.020177e-06 3.725609e-06 1.095994e-05
[576] 8.433567e-05 8.830902e-06 4.100741e-05 2.332971e-06 1.766942e-05
[581] 2.750329e-05 1.608203e-05 0.000000e+00 3.423805e-06 4.161766e-06
[586] 1.912386e-05 3.497199e-06 1.135134e-06 5.154947e-05 2.032366e-06
[591] 3.618524e-05 1.738401e-06 1.504797e-05 0.000000e+00 1.432317e-05
[596] 1.287074e-04 1.352456e-04 0.000000e+00 0.000000e+00 2.471976e-04
[601] 9.402089e-05 1.241123e-04 1.376398e-04 3.708738e-06 6.668610e-05
[606] 5.172756e-05 0.000000e+00 0.000000e+00 4.911430e-05 1.372071e-05
[611] 4.282081e-05 3.007979e-06 2.425608e-06 9.940653e-06 3.274889e-05
[616] 3.067379e-05 2.610620e-05 8.506420e-07 0.000000e+00 0.000000e+00
[621] 3.894909e-07 0.000000e+00 7.135924e-06 9.377978e-06 6.011008e-06
[626] 6.183942e-06 0.000000e+00 0.000000e+00 4.505872e-06 1.224464e-06
[631] 8.338429e-06 7.982276e-06 8.583409e-06 0.000000e+00 1.847454e-06
[636] 1.853963e-06 0.000000e+00 4.627350e-07 0.000000e+00 2.740414e-06
[641] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[646] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 6.727581e-06
[651] 7.455477e-06 0.000000e+00 0.000000e+00 1.170682e-05 3.626642e-06
[656] 7.436425e-06 8.589950e-06 2.410434e-06 3.278098e-06 1.748801e-05
[661] 0.000000e+00 2.479976e-06 4.985617e-06 3.490840e-06 9.687318e-06
[666] 0.000000e+00 3.766495e-06 7.199609e-06 4.846798e-06 2.069158e-06
[671] 0.000000e+00 0.000000e+00 0.000000e+00 2.353947e-06 4.215009e-06
[676] 0.000000e+00 3.125648e-06 0.000000e+00 0.000000e+00 2.440154e-07
[681] 0.000000e+00 1.407476e-06 0.000000e+00 0.000000e+00 0.000000e+00
[686] 1.960588e-05 1.444394e-05 4.267661e-06 0.000000e+00 0.000000e+00
[691] 9.616178e-06 0.000000e+00 0.000000e+00 3.458322e-06 1.036697e-05
[696] 3.921581e-06 1.052763e-05 1.879473e-05 9.629530e-06 0.000000e+00
[701] 7.805829e-08 9.255761e-06 9.267405e-06 2.108747e-07 5.538466e-06
[706] 0.000000e+00 5.482247e-07 5.751518e-07 8.759901e-06 1.463664e-06
[711] 2.051724e-06 1.185010e-06 3.379407e-06 3.086581e-06 1.272268e-05
[716] 7.729657e-06 2.133420e-05 1.830403e-05 0.000000e+00 0.000000e+00
[721] 2.605597e-06 0.000000e+00 3.661522e-06 0.000000e+00 0.000000e+00
[726] 4.268635e-06 0.000000e+00 4.727367e-06 0.000000e+00 0.000000e+00
[731] 0.000000e+00 0.000000e+00 0.000000e+00 2.304801e-05 0.000000e+00
[736] 7.089233e-06 0.000000e+00 0.000000e+00 5.617590e-09 5.531902e-06
[741] 6.294087e-09 0.000000e+00 2.258338e-06 4.117175e-06 4.335455e-06
[746] 7.170801e-06 0.000000e+00 3.186375e-06 0.000000e+00 7.303053e-06
[751] 1.947309e-07 1.040911e-07 3.124760e-06 0.000000e+00 0.000000e+00
[756] 3.006607e-07 0.000000e+00 0.000000e+00 0.000000e+00 1.921592e-08
[761] 3.051609e-06 3.403144e-06 5.997199e-06 3.740715e-06 5.649699e-06
[766] 1.104423e-06 0.000000e+00 0.000000e+00 8.085860e-07 4.421593e-06
[771] 0.000000e+00 1.862667e-06 4.321395e-06 0.000000e+00 0.000000e+00
[776] 5.102873e-06 0.000000e+00 9.336814e-06 4.565762e-06 2.513655e-06
[781] 3.520340e-06 4.471704e-06 3.963451e-06 1.965315e-06 0.000000e+00
[786] 8.865702e-06 1.255851e-06 0.000000e+00 7.457864e-05 7.227548e-06
[791] 4.479815e-05 9.601754e-06 0.000000e+00 0.000000e+00 0.000000e+00
[796] 3.799548e-06 4.736736e-06 1.454431e-07 1.920737e-05 4.816386e-06
[801] 0.000000e+00 0.000000e+00 9.442849e-06 2.249102e-06 3.745219e-06
[806] 0.000000e+00 0.000000e+00 4.125456e-06 2.047304e-08 2.925340e-05
[811] 4.699611e-06 0.000000e+00 9.432267e-06 0.000000e+00 9.619192e-06
[816] 1.617116e-07 1.124619e-06 2.017038e-06 6.497257e-06 8.710279e-06
[821] 6.307661e-06 6.859195e-06 1.226197e-06 3.920858e-06 5.552457e-06
[826] 6.768849e-06 3.789098e-06 5.550697e-06 6.002350e-06 8.371402e-06
[831] 1.086073e-06 3.674494e-06 4.354554e-07 2.357959e-06 7.377335e-06
[836] 1.713117e-07 2.049648e-06 7.736393e-06 3.749349e-06 0.000000e+00
[841] 0.000000e+00 5.745651e-07 0.000000e+00 0.000000e+00 1.754415e-05
[846] 3.859004e-06 3.667662e-06 3.947450e-06 9.207111e-06 2.313027e-06
[851] 0.000000e+00 4.030641e-08 3.617610e-06 0.000000e+00 3.577230e-06
[856] 3.024404e-06 3.739438e-06 3.262656e-06 8.325032e-06 2.520537e-06
[861] 1.552405e-06 5.043341e-06 7.867858e-06 1.060877e-05 1.016235e-06
[866] 6.924554e-06 1.594249e-05 8.205538e-05 8.240851e-06 8.930979e-06
[871] 2.663288e-06 0.000000e+00 1.627521e-06 2.868906e-06 2.471895e-06
[876] 4.440295e-06 1.193367e-05 3.732174e-06 1.640823e-07 0.000000e+00
[881] 2.107131e-06 0.000000e+00 0.000000e+00 0.000000e+00 7.814932e-08
[886] 6.236997e-07 3.349957e-06 0.000000e+00 0.000000e+00 0.000000e+00
[891] 1.413389e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[896] 2.854377e-06 2.011235e-05 9.155974e-05 1.367190e-05 3.607512e-06
[901] 6.398719e-06 6.038907e-06 0.000000e+00 2.956442e-06 0.000000e+00
[906] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[911] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[916] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[921] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[926] 0.000000e+00 0.000000e+00 3.747157e-06 3.123443e-06 0.000000e+00
[931] 0.000000e+00 9.686912e-06 0.000000e+00 0.000000e+00 4.048532e-06
[936] 1.055463e-07 0.000000e+00 4.369656e-06 0.000000e+00 1.372728e-06
[941] 7.835449e-06 0.000000e+00 1.265815e-05 0.000000e+00 1.001340e-06
[946] 0.000000e+00 1.487795e-05 3.435815e-06 1.056882e-06 7.988634e-06
[951] 6.430499e-06 0.000000e+00 6.260246e-06 2.971334e-06 0.000000e+00
[956] 1.494059e-06 0.000000e+00 6.550174e-06 3.092895e-09 1.529170e-05
[961] 4.426073e-06 6.827853e-06 3.586087e-06 1.548083e-05 2.076982e-06
[966] 4.724306e-06 3.083290e-06 0.000000e+00 8.170764e-06 1.149151e-06
[971] 6.517128e-06 0.000000e+00 1.084625e-06 0.000000e+00 2.717241e-06
[976] 3.740510e-06 6.017125e-06 4.863788e-06 3.670176e-06 0.000000e+00
[981] 3.638368e-06 9.687339e-06 4.900084e-06 3.660485e-05 3.902522e-06
[986] 0.000000e+00 8.758138e-05 4.601833e-06 0.000000e+00 3.496610e-06
[991] 0.000000e+00 2.502101e-06 2.880829e-06 0.000000e+00 0.000000e+00
[996] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1001] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1006] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1011] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1016] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1021] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1026] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1031] 0.000000e+00 0.000000e+00 4.959044e-06 0.000000e+00 2.501961e-06
[1036] 0.000000e+00 0.000000e+00 8.466738e-06 2.573130e-06 2.210468e-06
[1041] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.094212e-08
[1046] 2.720533e-06 7.717005e-07 6.914976e-07 9.227256e-06 1.990038e-06
[1051] 7.579180e-06 9.621465e-06 8.733854e-06 4.115690e-06 9.461154e-06
[1056] 1.242015e-06 9.554066e-06 0.000000e+00 9.698894e-06 3.868193e-06
[1061] 3.574705e-06 9.337434e-06 9.238164e-06 9.284323e-06 1.096687e-05
[1066] 5.108662e-06 3.964253e-07 0.000000e+00 8.372807e-06 1.097866e-05
[1071] 7.376724e-06 1.806999e-05 6.850265e-06 0.000000e+00 0.000000e+00
[1076] 6.836927e-06 1.244424e-05 5.377479e-05 4.524703e-05 3.903871e-05
[1081] 1.927536e-05 2.283063e-05 8.115519e-05 0.000000e+00 3.708554e-06
[1086] 1.896756e-05 3.630940e-06 3.591860e-06 0.000000e+00 1.025666e-05
[1091] 0.000000e+00 3.273071e-07 1.536952e-06 7.485753e-06 7.501334e-06
[1096] 4.030346e-06 5.256450e-05 9.525230e-06 0.000000e+00 1.235558e-06
[1101] 0.000000e+00 0.000000e+00 8.991048e-07 2.664112e-06 1.489013e-06
[1106] 1.421001e-05 1.280495e-05 2.474879e-06 1.283032e-05 3.722643e-06
[1111] 1.008733e-06 2.697892e-06 1.505169e-06 4.666887e-06 4.524922e-06
[1116] 3.948557e-06 4.140676e-06 4.405025e-06 8.556950e-06 3.968006e-06
[1121] 1.773954e-06 0.000000e+00 7.802542e-06 5.493989e-06 3.863634e-06
[1126] 7.354373e-06 5.432765e-08 3.100760e-06 0.000000e+00 4.764194e-06
[1131] 0.000000e+00 2.666943e-06 3.331003e-06 0.000000e+00 4.947588e-06
[1136] 0.000000e+00 2.301357e-06 0.000000e+00 1.535419e-05 0.000000e+00
[1141] 0.000000e+00 1.007240e-05 9.691280e-06 5.401058e-07 9.043236e-06
[1146] 3.215392e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1151] 0.000000e+00 1.729024e-07 3.651383e-07 0.000000e+00 0.000000e+00
[1156] 0.000000e+00 0.000000e+00 5.875062e-07 1.435312e-06 3.177164e-06
[1161] 0.000000e+00 0.000000e+00 2.158723e-05 8.528457e-07 2.442921e-05
[1166] 5.316566e-05 6.807505e-05 2.879773e-05 1.314666e-06 0.000000e+00
[1171] 3.324258e-06 3.847350e-05 4.877160e-06 4.562509e-05 4.559455e-05
[1176] 4.430452e-05 0.000000e+00 1.843016e-05 3.831633e-05 2.960856e-05
[1181] 4.681160e-05 9.157900e-06 7.383487e-07 6.572735e-06 1.370759e-05
[1186] 9.980888e-06 2.835253e-05 0.000000e+00 2.307092e-05 0.000000e+00
[1191] 1.430160e-05 1.697811e-05 2.644459e-05 3.361963e-05 2.332466e-07
[1196] 5.308175e-07 2.979205e-07 7.572440e-05 0.000000e+00 0.000000e+00
[1201] 1.545340e-05 2.484390e-05 3.170395e-05 4.780780e-05 3.198769e-06
[1206] 0.000000e+00 3.480590e-05 0.000000e+00 2.631263e-05 0.000000e+00
[1211] 1.444296e-07 2.205125e-05 5.529578e-05 3.287349e-06 3.553750e-07
[1216] 0.000000e+00 2.142538e-05 0.000000e+00 1.423006e-05 1.457571e-05
[1221] 3.797000e-05 5.189542e-07 4.152260e-06 5.688987e-06 4.042331e-05
[1226] 1.313076e-05 7.187810e-06 1.225415e-05 6.102072e-06 4.106682e-05
[1231] 1.284984e-05 3.871174e-05 4.217883e-05 6.758726e-05 4.345517e-05
[1236] 5.511778e-08 4.776837e-05 7.437551e-05 2.457924e-05 9.230154e-05
[1241] 2.286034e-05 3.500442e-05 3.877875e-05 4.866544e-05 3.959637e-07
[1246] 3.719430e-05 3.141010e-05 2.749858e-05 1.227374e-05 6.551409e-05
[1251] 5.483832e-05 1.965011e-05 2.455727e-05 1.978017e-05 2.168050e-05
[1256] 9.384770e-06 3.157500e-05 7.930150e-06 1.406884e-05 8.897518e-06
[1261] 4.412012e-06 5.098368e-06 1.721262e-05 1.858816e-05 2.184968e-05
[1266] 3.970473e-06 4.189532e-06 0.000000e+00 0.000000e+00 3.821812e-06
[1271] 0.000000e+00 2.978193e-05 1.786938e-05 3.811503e-05 1.739178e-05
[1276] 2.679383e-05 0.000000e+00 1.279369e-07 0.000000e+00 2.667955e-05
[1281] 0.000000e+00 1.736218e-05 1.217707e-05 0.000000e+00 0.000000e+00
[1286] 2.258547e-05 0.000000e+00 2.880048e-05 1.091095e-05 3.855634e-06
[1291] 1.462699e-05 2.109495e-05 3.381224e-05 1.435928e-05 2.273874e-05
[1296] 6.724471e-06 1.765301e-05 6.553831e-06 1.788093e-05 0.000000e+00
[1301] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1306] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1311] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1316] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1321] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 3.339525e-06
[1326] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.453155e-05
[1331] 1.074524e-07 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1336] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1341] 0.000000e+00 0.000000e+00 2.253636e-05 0.000000e+00 0.000000e+00
[1346] 3.207159e-05 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1351] 0.000000e+00 2.960092e-08 1.071708e-05 6.555440e-06 1.622711e-05
[1356] 4.157138e-05 1.545956e-05 0.000000e+00 3.478733e-05 3.502830e-05
[1361] 4.402226e-05 2.485322e-05 2.372626e-05 0.000000e+00 0.000000e+00
[1366] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1371] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1376] 2.579900e-05 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1381] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.664967e-05
[1386] 2.664352e-05 0.000000e+00 0.000000e+00 0.000000e+00 3.432754e-05
[1391] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 3.566006e-05
[1396] 3.212144e-06 3.091614e-05 3.480470e-05 0.000000e+00 0.000000e+00
[1401] 4.759787e-05 2.599756e-05 2.397522e-05 6.810297e-06 1.583431e-05
[1406] 7.351839e-06 5.712610e-05 5.840281e-06 1.579779e-05 3.212593e-06
[1411] 5.690670e-07 4.289688e-06 1.547419e-05 9.886393e-07 6.953264e-06
[1416] 1.615551e-06 0.000000e+00 0.000000e+00 9.386392e-06 0.000000e+00
[1421] 1.962251e-05 1.094499e-05 3.699398e-04 1.283798e-04 1.529716e-04
[1426] 0.000000e+00 0.000000e+00 0.000000e+00 1.211489e-06 5.645676e-06
[1431] 1.584703e-04 3.368536e-06 0.000000e+00 0.000000e+00 0.000000e+00
[1436] 8.109978e-07 0.000000e+00 0.000000e+00 0.000000e+00 6.507394e-07
[1441] 3.685815e-05 1.189800e-06 0.000000e+00 9.658384e-06 2.265937e-05
[1446] 7.164876e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[1451] 1.297789e-06 2.966729e-06 0.000000e+00 0.000000e+00 3.249372e-06
[1456] 3.556397e-06 1.476207e-05 5.578903e-06 0.000000e+00 5.902451e-05
[1461] 3.157554e-06 1.789411e-05 7.961534e-06 4.074571e-06 0.000000e+00
[1466] 0.000000e+00 5.699068e-06 1.413960e-04 1.051345e-04 1.591135e-04
[1471] 0.000000e+00 9.901214e-05 9.986561e-05 3.568068e-05 4.147215e-05
[1476] 1.673891e-05 1.785747e-05 3.167934e-06 2.367510e-05 0.000000e+00
[1481] 0.000000e+00 0.000000e+00 0.000000e+00 9.655755e-06 9.991547e-06
[1486] 6.426808e-06 4.855516e-05 0.000000e+00 1.364082e-04 3.539170e-05
[1491] 1.090235e-05 0.000000e+00 1.397525e-04 4.242856e-07 6.058276e-06
[1496] 2.137954e-05 1.028563e-05 2.791478e-05 4.595720e-07 5.902218e-06
[1501] 2.970427e-06 4.995913e-08 0.000000e+00 3.578818e-05 7.217125e-06
[1506] 1.283008e-06 0.000000e+00 1.505284e-06 0.000000e+00 0.000000e+00
[1511] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 9.684729e-06
[1516] 0.000000e+00 9.006791e-06 0.000000e+00 1.131927e-05 3.561390e-06
[1521] 1.346611e-06 1.066539e-05 9.078694e-06 1.008374e-05 1.618492e-05
[1526] 3.667811e-06 1.820640e-06 1.315073e-05 3.335104e-06 1.386509e-06
[1531] 0.000000e+00 0.000000e+00 0.000000e+00 8.663905e-06 2.621818e-04
[1536] 3.190539e-05 3.753071e-04 0.000000e+00 6.346675e-05 1.574142e-04
[1541] 1.420098e-05 5.415504e-05 6.547553e-05 1.091830e-04 6.436195e-05
[1546] 1.981958e-05 3.391083e-05 5.670268e-05 1.018226e-04 1.458385e-04
[1551] 8.806128e-05 1.327745e-05 1.317653e-04 4.147015e-06 0.000000e+00
[1556] 0.000000e+00 1.556016e-06 0.000000e+00 0.000000e+00 0.000000e+00
[1561] 9.423889e-07 6.788425e-06 0.000000e+00 7.023903e-06 6.331277e-06
[1566] 1.891864e-06 0.000000e+00 0.000000e+00 3.733300e-06 0.000000e+00
[1571] 0.000000e+00 6.237838e-06 5.411998e-06 2.505543e-06 1.080280e-06
[1576] 0.000000e+00 3.739567e-06 0.000000e+00 4.411859e-09 0.000000e+00
[1581] 1.183030e-05 6.279318e-08 0.000000e+00 3.226706e-06 6.556032e-07
[1586] 2.964958e-08 7.163885e-07 1.410040e-07 4.097082e-06 1.357026e-06
[1591] 6.449696e-07 0.000000e+00 1.296498e-06 0.000000e+00 2.319603e-07
[1596] 0.000000e+00 0.000000e+00 0.000000e+00 3.422150e-06 0.000000e+00
[1601] 1.743932e-06 0.000000e+00 0.000000e+00 0.000000e+00 3.658896e-06
[1606] 0.000000e+00 2.598763e-06 0.000000e+00 2.429793e-05 1.455416e-04
[1611] 1.462037e-04 1.316248e-06samples_bangkok$density <- nkde_result_bangkok
lixels_bangkok$density <- nkde_result_bangkok
# 重新缩放密度值（从每米事件数量调整为每公里事件数量）
samples_bangkok$density <- samples_bangkok$density * 10000
lixels_bangkok$density <- lixels_bangkok$density * 10000
# 将 nkde_result_pathum_thani 赋值给 sample_pathum_thani 和 lixels_pathum_thani 的 density 列
samples_SamutPrakan$density <- nkde_result_SamutPrakan
lixels_SamutPrakan$density <- nkde_result_SamutPrakan
# 重新缩放密度值（从每米事件数量调整为每公里事件数量）
samples_SamutPrakan$density <- samples_SamutPrakan$density * 10000
lixels_SamutPrakan$density <- lixels_SamutPrakan$density * 100008.map：
# 绘制 Bangkok
tm_shape(lixels_bangkok) +
tm_lines(col = "density", palette = "-RdYlBu", title.col = "Density", lwd = 3, breaks = c(0, 0.1, 0.2, 0.3, 0.4, 0.5)) +
tm_shape(acc_in_bangkok) +
tm_dots(size = 0.1, col = "blue", alpha = 0.5, title = "Accidents")